Define Types of image resolution.

Image resolution refers to the level of detail, clarity, and sharpness in an image. It is a critical aspect of digital imagery and impacts the quality and precision of visual and analytical interpretations. There are several types of image resolution, each serving specific purposes in different applications:

1. Spatial Resolution:
   Spatial resolution refers to the level of detail or ground coverage represented by each pixel in an image. It is usually measured in terms of meters per pixel or centimeters per pixel on the Earth's surface. Higher spatial resolution indicates finer details and is essential for applications such as land cover mapping, urban planning, and infrastructure monitoring.

2. Spectral Resolution:
   Spectral resolution relates to the ability of an imaging system to distinguish between different wavelengths or colors within the electromagnetic spectrum. A sensor with higher spectral resolution captures more bands, allowing for detailed spectral analysis. This is crucial in applications like vegetation health assessment, mineral identification, and environmental monitoring.

3. Temporal Resolution:
   Temporal resolution refers to the frequency at which an imaging system revisits or captures data for a specific location over time. It is critical for monitoring dynamic processes and changes on the Earth's surface. Satellites with high temporal resolution provide more frequent updates, supporting applications like agriculture monitoring, disaster response, and land-use change detection.

4. Radiometric Resolution:
   Radiometric resolution refers to the ability of a sensor to capture and represent variations in brightness levels or intensity values within an image. Higher radiometric resolution allows for a greater range of distinguishable tones or colors, enhancing the ability to differentiate subtle features. This is crucial for applications such as forestry analysis, terrain modeling, and precision agriculture.

5. Temporal-Spectral Resolution:
   Temporal-spectral resolution combines the aspects of both temporal and spectral resolutions. It focuses on the ability of an imaging system to capture data at frequent intervals and across multiple spectral bands. This is particularly beneficial for monitoring vegetation health, crop conditions, and environmental changes over time with detailed spectral information.

6. Angular Resolution:
   Angular resolution relates to the ability of a sensor to differentiate between objects or features that are close together in terms of their angular separation. It is often discussed in the context of remote sensing platforms like satellites or aircraft. Higher angular resolution allows for better discrimination of adjacent objects in the field of view.

Each type of resolution plays a crucial role in various applications, and the optimal combination depends on the specific requirements of a given task. Balancing these resolutions is essential for obtaining comprehensive and accurate information from remote sensing data, supporting applications across environmental monitoring, agriculture, forestry, urban planning, and disaster management.